flink-statefun
Apache Avro
flink-statefun | Apache Avro | |
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18 | 22 | |
495 | 2,790 | |
0.4% | 0.9% | |
3.2 | 9.7 | |
26 days ago | 3 days ago | |
Java | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
flink-statefun
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flink-statefun VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Snowflake - what are the streaming capabilities it provides?
When low latency matters you should always consider an ETL approach rather than ELT, e.g. collect data in Kafka and process using Kafka Streams/Flink in Java or Quix Streams/Bytewax in Python, then sink it to Snowflake where you can handle non-critical workloads (as is the case for 99% of BI/analytics). This way you can choose the right path for your data depending on how quickly it needs to be served.
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JR, quality Random Data from the Command line, part I
Sometimes we may need to generate random data of type 2 in different streams, so the "coherency" must also spread across different entities, think for example to referential integrity in databases. If I am generating users, products and orders to three different Kafka topics and I want to create a streaming application with Apache Flink, I definitely need data to be coherent across topics.
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Brand Lift Studies on Reddit
The Treatment and Control audiences need to be stored for future low-latency, high-reliability retrieval. Retrieval happens when we are delivering the survey, and informs the system which users to send surveys to. How is this achieved at Reddit’s scale? Users interact with ads, which generate events that are sent to our downstream systems for processing. At the output, these interactions are stored in DynamoDB as engagement records for easy access. Records are indexed on user ID and ad campaign ID to allow for efficient retrieval. The use of stream processing (Apache Flink) ensures this whole process happens within minutes, and keeps audiences up to date in real-time. The following high-level diagram summarizes the process:
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Query Real Time Data in Kafka Using SQL
Most streaming database technologies use SQL for these reasons: RisingWave, Materialize, KsqlDB, Apache Flink, and so on offering SQL interfaces. This post explains how to choose the right streaming database.
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How to choose the right streaming database
Apache Flink.
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5 Best Practices For Data Integration To Boost ROI And Efficiency
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka.
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Forward Compatible Enum Values in API with Java Jackson
We’re not discussing the technical details behind the deduplication process. It could be Apache Flink, Apache Spark, or Kafka Streams. Anyway, it’s out of the scope of this article.
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Which MQTT (or similar protocol) broker for a few 10k IoT devices with quite a lot of traffic?
One can also consider https://flink.apache.org/ instead of Kafka for connecting a large number of devices.
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Apache Pulsar vs Apache Kafka - How to choose a data streaming platform
Both Kafka and Pulsar provide some kind of stream processing capability, but Kafka is much further along in that regard. Pulsar stream processing relies on the Pulsar Functions interface which is only suited for simple callbacks. On the other hand, Kafka Streams and ksqlDB are more complete solutions that could be considered replacements for Apache Spark or Apache Flink, state-of-the-art stream-processing frameworks. You could use them to build streaming applications with stateful information, sliding windows, etc.
Apache Avro
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Open Table Formats Such as Apache Iceberg Are Inevitable for Analytical Data
Apache AVRO [1] is one but it has been largely replaced by Parquet [2] which is a hybrid row/columnar format
[1] https://avro.apache.org/
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Generating Avro Schemas from Go types
The most common format for describing schema in this scenario is Apache Avro.
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How do you update an existing avro schema using apache avro SchemaBuilder?
I am testing a new schema registry which loads and retrieves different kinds of avro schemas. In the process of testing, I need to create a bunch of different types of avro schemas. As it involves a lot of permutations, I decided to create the schema programmatically.I am using the apache avro SchemaBuilder to do so.
- The state of Apache Avro in Rust
- How people generate examples for multiple programming languages?
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gRPC on the client side
Other serialization alternatives have a schema validation option: e.g., Avro, Kryo and Protocol Buffers. Interestingly enough, gRPC uses Protobuf to offer RPC across distributed components:
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Understanding Azure Event Hubs Capture
Apache Avro is a data serialization system, for more information visit Apache Avro
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tl;dr of Data Contracts
Once things like JSON became more popular Apache Avro appeared. You can define Avro files which can then be generated into Python, Java C, Ruby, etc.. classes.
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In One Minute : Hadoop
Avro, a data serialization system based on JSON schemas.
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Events: Fat or Thin?
Supporting multiple versions of an event schema is a solved problem. Apache Avro with a published schema hash in a message header is one solution.
https://avro.apache.org/
What are some alternatives?
opensky-api - Python and Java bindings for the OpenSky Network REST API
Protobuf - Protocol Buffers - Google's data interchange format
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
SBE - Simple Binary Encoding (SBE) - High Performance Message Codec
debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.
Apache Thrift - Apache Thrift
redpanda - Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
iceberg - Apache Iceberg
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system
Apache Parquet - Apache Parquet
faust - Python Stream Processing. A Faust fork
gRPC - The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)